Look up R matrix cells in a vectorized way

Question

I'd like to lookup matrix cells by using rows and columns from a data frame. Preferably, I'd like to do this in a vectorized way for best performance. However, the most obvious syntax leads to a lookup of all the row-column combinations possible, not only the combinations that stem from one data frame row:

Here is a small example:

> m1 <- matrix(c(1, 2, 3, 4, 5, 6, 7, 8, 9), 3, 3)
> 
> m1
     [,1] [,2] [,3]
[1,]    1    4    7
[2,]    2    5    8
[3,]    3    6    9
> 
> p1 <- data.frame(row = c(2, 3, 1), column = c(3, 1, 2))
> 
> p1
  row column
1   2      3
2   3      1
3   1      2
> 
> # vectorized indexing that does not work as intended
> m1[p1$row, p1$column]
     [,1] [,2] [,3]
[1,]    8    2    5
[2,]    9    3    6
[3,]    7    1    4
> 
> # this works as intended, but is possible slow due to R-language looping
> sapply(1 : nrow(p1), function (i) { m1[p1[i, "row"], p1[i, "column"]] })
[1] 8 3 4

The sapply call computes the output I expect (only m1[2, 3] , m1[3, 1] and m1[1, 2] ), but it's expected to be slow for larger data frames because it loops in R language.

Any thoughts on a better (ideally vectorized) way?

Answer 1

For your intended purpose you need to use a matrix to subset the matrix using certain row,column combinations. So you can try:

m1[as.matrix(p1)]
# [1] 8 3 4

Or if you have two vectors:

m1[cbind(row_idx, col_idx)]